1. Field of Art
The present disclosure generally relates to the field of digital video, and more specifically, to methods of determining the semantic similarity of two images or portions thereof.
2. Background of the Disclosure
Automated analysis of images and videos has a number of useful applications. As one example, the ability to quantify the semantic similarity of images or objects therein would allow a user to search for images or videos similar to an image or video presently being viewed, or a system to identify a particular object across time within a video despite a change in its visual appearance.
However, conventional techniques rely on the existence of consistent visual similarity when comparing two visual objects or tracking an object over time. Although such techniques can be applied to objects with a consistent visual representation, they perform poorly in the case of objects that can deform (such as bursting balloons, or eyes that open and close over time), objects that are capable of articulated motion (such as people or animals), and other types of objects that can dramatically change their visual appearance over time.